{
 "cells": [
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   "execution_count": 1,
   "id": "616dcd3b-7498-4a0d-8369-dc6b528f044e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib.ticker import MultipleLocator\n",
    "from brokenaxes import brokenaxes\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04e5d265-f72d-4500-8985-f18caf94b571",
   "metadata": {
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   "outputs": [
    {
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       "      <th>algorithm</th>\n",
       "      <th>features</th>\n",
       "      <th>runtime</th>\n",
       "      <th>runtime/feat.</th>\n",
       "      <th>R2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fastprop</td>\n",
       "      <td>453</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tsflex</td>\n",
       "      <td>259</td>\n",
       "      <td>63.5</td>\n",
       "      <td>99.3</td>\n",
       "      <td>0.944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>featuretools</td>\n",
       "      <td>125</td>\n",
       "      <td>85.5</td>\n",
       "      <td>309.7</td>\n",
       "      <td>0.948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tsfel</td>\n",
       "      <td>378</td>\n",
       "      <td>254.3</td>\n",
       "      <td>304.8</td>\n",
       "      <td>0.308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tsfresh</td>\n",
       "      <td>84</td>\n",
       "      <td>47.7</td>\n",
       "      <td>257.0</td>\n",
       "      <td>0.781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>kats</td>\n",
       "      <td>189</td>\n",
       "      <td>482.7</td>\n",
       "      <td>1156.7</td>\n",
       "      <td>0.349</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      algorithm  features  runtime  runtime/feat.     R2\n",
       "0      fastprop       453      1.0            1.0  0.949\n",
       "1        tsflex       259     63.5           99.3  0.944\n",
       "2  featuretools       125     85.5          309.7  0.948\n",
       "3         tsfel       378    254.3          304.8  0.308\n",
       "4       tsfresh        84     47.7          257.0  0.781\n",
       "5          kats       189    482.7         1156.7  0.349"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pollution = pd.read_csv('paper_data.txt', skiprows=545, skipfooter=(733-552),\n",
    "                       engine='python', sep=' ')\n",
    "df_pollution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "38ff3423-fa3b-407c-9a99-7b4028774869",
   "metadata": {
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   "outputs": [
    {
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       "      <th>runtime/feat.</th>\n",
       "      <th>R2</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>fastprop</td>\n",
       "      <td>125</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tsflex</td>\n",
       "      <td>36</td>\n",
       "      <td>18.8</td>\n",
       "      <td>59.3</td>\n",
       "      <td>0.979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>featuretools</td>\n",
       "      <td>59</td>\n",
       "      <td>74.1</td>\n",
       "      <td>157.9</td>\n",
       "      <td>0.972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tsfel</td>\n",
       "      <td>54</td>\n",
       "      <td>97.1</td>\n",
       "      <td>224.8</td>\n",
       "      <td>0.876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tsfresh</td>\n",
       "      <td>12</td>\n",
       "      <td>20.7</td>\n",
       "      <td>215.8</td>\n",
       "      <td>0.172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>kats</td>\n",
       "      <td>27</td>\n",
       "      <td>141.1</td>\n",
       "      <td>653.3</td>\n",
       "      <td>0.941</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      algorithm  features  runtime  runtime/feat.     R2\n",
       "0      fastprop       125      1.0            1.0  0.979\n",
       "1        tsflex        36     18.8           59.3  0.979\n",
       "2  featuretools        59     74.1          157.9  0.972\n",
       "3         tsfel        54     97.1          224.8  0.876\n",
       "4       tsfresh        12     20.7          215.8  0.172\n",
       "5          kats        27    141.1          653.3  0.941"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_interstate = pd.read_csv('paper_data.txt', skiprows=554, skipfooter=(733-561),\n",
    "                       engine='python', sep=' ')\n",
    "df_interstate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ff6d5b05-3133-45ee-acca-ec1ea5c2d9ab",
   "metadata": {
    "tags": []
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   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>fastprop</td>\n",
       "      <td>207</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tsflex</td>\n",
       "      <td>38</td>\n",
       "      <td>14.8</td>\n",
       "      <td>70.9</td>\n",
       "      <td>0.802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>featuretools</td>\n",
       "      <td>59</td>\n",
       "      <td>57.3</td>\n",
       "      <td>201.1</td>\n",
       "      <td>0.794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tsfel</td>\n",
       "      <td>54</td>\n",
       "      <td>74.5</td>\n",
       "      <td>285.5</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tsfresh</td>\n",
       "      <td>12</td>\n",
       "      <td>14.8</td>\n",
       "      <td>255.6</td>\n",
       "      <td>0.667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>kats</td>\n",
       "      <td>27</td>\n",
       "      <td>95.6</td>\n",
       "      <td>732.6</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      algorithm  features  runtime  runtime/feat.     R2\n",
       "0      fastprop       207      1.0            1.0  0.795\n",
       "1        tsflex        38     14.8           70.9  0.802\n",
       "2  featuretools        59     57.3          201.1  0.794\n",
       "3         tsfel        54     74.5          285.5  0.000\n",
       "4       tsfresh        12     14.8          255.6  0.667\n",
       "5          kats        27     95.6          732.6  0.001"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dodgers = pd.read_csv('paper_data.txt', skiprows=580, skipfooter=(733-587),\n",
    "                       engine='python', sep=' ')\n",
    "df_dodgers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c6054cbd-52d6-4059-a5c6-408de3d07d9f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fastprop</td>\n",
       "      <td>1273.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tsflex</td>\n",
       "      <td>1058.0</td>\n",
       "      <td>87.1</td>\n",
       "      <td>108.6</td>\n",
       "      <td>0.114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>featuretools</td>\n",
       "      <td>367.0</td>\n",
       "      <td>77.7</td>\n",
       "      <td>269.7</td>\n",
       "      <td>0.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tsfel</td>\n",
       "      <td>1566.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>58.5</td>\n",
       "      <td>0.114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tsfresh</td>\n",
       "      <td>348.0</td>\n",
       "      <td>59.3</td>\n",
       "      <td>217.0</td>\n",
       "      <td>0.108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>kats1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      algorithm  features  runtime  runtime/feat.     R2\n",
       "0      fastprop    1273.0      1.0            1.0  0.171\n",
       "1        tsflex    1058.0     87.1          108.6  0.114\n",
       "2  featuretools     367.0     77.7          269.7  0.100\n",
       "3         tsfel    1566.0     72.0           58.5  0.114\n",
       "4       tsfresh     348.0     59.3          217.0  0.108\n",
       "5         kats1       NaN      NaN            NaN    NaN"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_energy = pd.read_csv('paper_data.txt', skiprows=589, skipfooter=(733-596),\n",
    "                       engine='python', sep=' ')\n",
    "df_energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "089598c0-9daa-4d54-a970-7d7b33668eaa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "      <th>R2</th>\n",
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       "      <th>0</th>\n",
       "      <td>fastprop</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tsflex</td>\n",
       "      <td>296</td>\n",
       "      <td>69.8</td>\n",
       "      <td>85.1</td>\n",
       "      <td>0.996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>featuretools</td>\n",
       "      <td>136</td>\n",
       "      <td>88.1</td>\n",
       "      <td>266.9</td>\n",
       "      <td>0.981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tsfel</td>\n",
       "      <td>432</td>\n",
       "      <td>275.6</td>\n",
       "      <td>262.8</td>\n",
       "      <td>0.983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tsfresh</td>\n",
       "      <td>96</td>\n",
       "      <td>52.9</td>\n",
       "      <td>227.0</td>\n",
       "      <td>0.940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>kats</td>\n",
       "      <td>216</td>\n",
       "      <td>556.5</td>\n",
       "      <td>1061.5</td>\n",
       "      <td>0.978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      algorithm  features  runtime  runtime/feat.     R2\n",
       "0      fastprop       412      1.0            1.0  0.997\n",
       "1        tsflex       296     69.8           85.1  0.996\n",
       "2  featuretools       136     88.1          266.9  0.981\n",
       "3         tsfel       432    275.6          262.8  0.983\n",
       "4       tsfresh        96     52.9          227.0  0.940\n",
       "5          kats       216    556.5         1061.5  0.978"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tetouan = pd.read_csv('paper_data.txt', skiprows=617, skipfooter=(733-624),\n",
    "                       engine='python', sep=' ')\n",
    "df_tetouan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "105c4ad1-79a5-4050-95c2-11b3888709af",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_axis = np.arange(len(df_pollution['algorithm']))\n",
    "\n",
    "height = 0.12\n",
    "\n",
    "plt.figure(dpi=120)\n",
    "\n",
    "plt.barh(x_axis, df_pollution['runtime/feat.'], height=height, label='Air Pollution')\n",
    "plt.barh(x_axis + height, df_interstate['runtime/feat.'], height=height, label='Insterstate94')\n",
    "plt.barh(x_axis + (2*height), df_dodgers['runtime/feat.'], height=height, label='Dodgers')\n",
    "plt.barh(x_axis + (3*height), df_energy['runtime/feat.'], height=height, label='Energy')\n",
    "plt.barh(x_axis + (4*height), df_tetouan['runtime/feat.'], height=height, label='Tetouan')\n",
    "\n",
    "plt.gca().xaxis.set_minor_locator(MultipleLocator(100))\n",
    "\n",
    "plt.yticks(x_axis, df_pollution['algorithm'])\n",
    "plt.xlabel('Runtime / Feature')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "db8f9e5c-74e5-4ca8-ab42-8c42fd1d6541",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_axis = np.arange(len(df_pollution['algorithm']))\n",
    "\n",
    "width = 0.1\n",
    "\n",
    "plt.figure(dpi=120)\n",
    "\n",
    "plt.bar(x_axis, df_pollution['runtime/feat.'], width=width, label='Air Pollution')\n",
    "plt.bar(x_axis + width, df_interstate['runtime/feat.'], width=width, label='Insterstate94')\n",
    "plt.bar(x_axis + (2*width), df_dodgers['runtime/feat.'], width=width, label='Dodgers')\n",
    "plt.bar(x_axis + (3*width), df_energy['runtime/feat.'], width=width, label='Energy')\n",
    "plt.bar(x_axis + (4*width), df_tetouan['runtime/feat.'], width=width, label='Tetouan')\n",
    "\n",
    "plt.gca().yaxis.set_minor_locator(MultipleLocator(100))\n",
    "\n",
    "plt.xticks(x_axis, df_pollution['algorithm'])\n",
    "plt.ylabel('Runtime / Feature')\n",
    "plt.legend()\n",
    "plt.savefig('../assets/benchmarks_plot.png');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "33037788-b647-451f-91f6-967a502de159",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_axis = np.arange(len(df_pollution['algorithm']))\n",
    "\n",
    "width = 0.1\n",
    "\n",
    "plt.figure(dpi=120)\n",
    "\n",
    "baxes = brokenaxes(ylims=((1,400),(600,1200)))\n",
    "\n",
    "baxes.bar(x_axis, df_pollution['runtime/feat.'], width=width, label='Air Pollution')\n",
    "baxes.bar(x_axis + width, df_interstate['runtime/feat.'], width=width, label='Insterstate94')\n",
    "baxes.bar(x_axis + (2*width), df_dodgers['runtime/feat.'], width=width, label='Dodgers')\n",
    "baxes.bar(x_axis + (3*width), df_energy['runtime/feat.'], width=width, label='Energy')\n",
    "baxes.bar(x_axis + (4*width), df_tetouan['runtime/feat.'], width=width, label='Tetouan')\n",
    "\n",
    "# plt.gca().yaxis.set_minor_locator(MultipleLocator(100))\n",
    "\n",
    "baxes.set_xticks(x_axis, df_pollution['algorithm'])\n",
    "baxes.set_ylabel('Runtime / Feature')\n",
    "\n",
    "baxes.legend(loc='upper left');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3d738228-ae06-4269-914b-f51732baaca3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_axis = np.arange(len(df_pollution['algorithm']))\n",
    "\n",
    "width = 0.1\n",
    "\n",
    "plt.figure(dpi=120)\n",
    "\n",
    "plt.bar(x_axis, df_pollution['runtime/feat.'], width=width, label='Air Pollution')\n",
    "plt.bar(x_axis + width, df_interstate['runtime/feat.'], width=width, label='Insterstate94')\n",
    "plt.bar(x_axis + (2*width), df_dodgers['runtime/feat.'], width=width, label='Dodgers')\n",
    "plt.bar(x_axis + (3*width), df_energy['runtime/feat.'], width=width, label='Energy')\n",
    "plt.bar(x_axis + (4*width), df_tetouan['runtime/feat.'], width=width, label='Tetouan')\n",
    "\n",
    "plt.xticks(x_axis, df_pollution['algorithm'])\n",
    "plt.ylabel('Runtime / Feature')\n",
    "plt.yscale('log')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1bf3712c-cdec-42c4-81c9-c76270baf702",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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eMFcF+Ao4zzn3bi7l7PHvWfwQcBXeHVSWAt2cc/PyWAcRERGRw1pQLYT3kzUgTMBrzesOfAe8mdeNOuf2Arf6j+zytM8mfRPevY9FREREJAeBBITOuZTslpnZkcDHwPdBlCUiIiIiwSrwQSXOuY3AU8A9BV2WiIiIiORdYY0y3g00KKSyRERERCQPCjwgNLNmwDB0yVhEREQkJgU1yngNkUcZVwYqAX/gDS4RERERkRgT1Cjjd8gaEDrgN2AVMM05ty2gskREREQkQEGNMu6fWx4zq+Cc2xVEeSIiIiISnMLoQ1jDzEbh3S1ERERERGJMvloI/VvK9QUa4V0enumc+8JfVhu4G29y6ERgcX7KEhEREZGCccgBoZkdC7wLVOOv+wjfZma98foPPoMXCM4EHk4PFEVEREQktuSnhXAkkAQMAd7Dm2fwUWAc3sjiN4A7nHOr81lHERERESlA+QkIzwSedM497b9eYWYHgDnAFOfcgHzXTkREREQKXH4GlVQDvgpL+5///Go+tisiIiIihSg/AWEJYH9YWvrr3/OxXREREREpRPmdh7CVme0NeV0Bb0BJWzOrHJ7ZOfdKPssTERERkYDlNyC80X+ES4mQ5oCEfJYnIiIiIgHLT0DYIbBaiIiIiEiRyU9A+L5zLi2wmoiIiIhIkcjPoJKtZvYfM+tjZsmB1UhEREREClV+AsJ7gIrA08BGM/vEzEaYWctgqiYiIiIiheGQA0Ln3HjnXFe8+QgvAr4ArgI+M7OfzezfZnaxmVUIqK4iIiIiUgDyO8oY59wevNvUvQFgZs2AbkBXYBrgzOx94C1gtnPu2/yWKSIiIiLByc8l44icc8uccw8659oDyUAf4EfgVmC5md0edJkiIiIicujy3UKYE+fcDmC6/8DMTinI8kREREQk7wIJCP1+gpWdcz+GpNUCBgNlgBnOuc+cc58FUZ6IiIiIBCeoFsJJQAPgVAAzqwh8DNQBDgI3mNk5zrnFAZUnIiIiIgEJqg9hW+DNkNe9gVrA6UAV4CtgeEBliYiIiEiAggoIqwMbQl5fgHcnk4+dc7uA54ETAipLRERERAIUVEC4HTgCwMzKAu2A+SHLDwDlAipLRERERAIUVB/CD4EhZvYtcA6QCLwesrwJmVsQRURERCRGBBUQ3o7XIjjTfz3WObccwMwSgJ7A3IDKEhEREZEABRIQOud+MLNjgOOBHc65tSGLywFDgf8FUZaIiIiIBCuwiamdc/uJEPT5g0pez7qGiIiIiMSCwG5dZ2YVzewOM5tnZl+aWWs/vaqZ3WxmjYMqS0RERESCE9SdSuoA7wBHASuBY4EkAOfcNjMbBNQDbgiiPBEREREJTlCXjB8GKgAnApv8R6jXgPMCKktEREREAhTUJeOzgcedcysAF2H5arzWQxERERGJMUEFhGWBzTksrxBQOSIiIiISsKACwhXAmTks7w58GVBZIiIiIhKgoALCcUAvM7sdqJS+bTNrbGZTgdOARwMqS0REREQCFNTE1C+YWT3gH8A//eS5gAEHgbucc68FUZaIiIiIBCvIian/6bcGXgI0xmt9XAW84pxbHVQ5IiIiIhKsfAeEZlYOeA/4l3PuKXRpWERERKRYyXcfQufcH0ADIk83IyIiIiIxLqhBJXOBLgFtS0REREQKUVAB4UigiZlNNbO2Zlbbv4dxpkdAZYmIiIhIgIIaVLLcfz4euCKHfAkBlSciIiIiAQkqILwf9SEUERERKZaCmocwJYjtiIiIiEjhC6oPoYiIiIgUU4G0EJrZiCiyOefcyCDKExEREZHgBNWHMCWHZQ7vFnYObzSyiIiIiMSQQC4ZO+dKhD/wgs1GeHcu+RyoEURZIiIiIhKswO5lHM45dxBYA9xiZqnAeHKekkZEYpxzjt27d7Nz50727duHc5pcQGKHmZGUlESVKlUoWbLAft5EDkuFNajkXeDcQipLRAqAc45Nmzbx448/smPHDtLS0oq6SiKZ7N+/ny1btrBhwwb9syKSR4X1L1Qr4GBeVzKzMnhzHPYBqgBfAcOdcwvyuJ0FQCdggnNuaF7rISKwe/dutm3bRrly5TjyyCMpXbp0UVdJJBPnHBs3bmTHjh3s2rWLihUrFnWVRIqNoEYZ981mUWXgTOBi4JlD2PRkoAcwDlgJ9AfeMrMOzrn3o6zbxcBph1C2iITYuXMngIJBiVlmRo0aNdixYwc7d+5UQCiSB0G1EE7OYdkW4AG8lr6omVlroBdwq3NujJ/2PLAMeAg4PYptJAJjgQfzWr6IZLZv3z5KlSqlYFBiWsmSJSlZsiT79+8v6qqIFCtBBYQNIqQ54Dfn3K5D3GYPIA2YlLFB5/aa2bPAKDM7yjn3Yy7buA2vn+QYFBCK5ItzjhIlNJe9xL4SJUqoD6FIHgUVEDpgs3NuT6SFZlYWSHbOrc/DNk8CvnfO7QxL/9R/PhHINiA0s7rAHcBVzrk9ZpaHokVEpLjS+V4k74IKCNfgDfx4MZvlF/jLEvKwzSOBjRHS09Nq5bL+WOBL59y0PJQJgJnVAJLDkhvldTsiIiIixUFQ139y+3esFHkfZVwW2BchfW/I8siVMesAXALcmMcy0w3B66sY+nj9ELclIochMyMlJaWoq5Ghf//+1K9fP1NaQdRx8uTJmBlr164NdLsiUrQOOSA0s4pmVte/NAtQLf112KMF3uCQSK19OdkDlImQnhiyPFK9SgKPA1Odc5/lscx0E4FmYY8LD3FbIlLMTJw4ETOjTZs2BVbG4sWLMbOMR6lSpWjYsCF9+/Zl9erVBVZutEaNGsVrr71W1NUQkUKSn0vGNwEj/L8d3tQw47LJa8DwPG5/I1A7QvqR/vPP2azXFzgGGGRm9cOWVfDTNjnn/siuYOfcJmBTaJr6pIjkrP4ds4u6Cqx9oFsg20lNTaV+/fp8+umn/PDDDzRu3DhLnj179gRyN4xhw4ZxyimnsH//fpYsWcKkSZOYPXs2X3/9NbVq5dYzpuCMGjWKHj160L1790zpffr0oVevXpQpE+n/dREprvJzNpsP/I4X7D0EvAQsCcvjgN3AF865z/O4/aVABzOrGDawpE3I8kjq4l2i/iDCsr7+4yLgtTzWR0TiwJo1a/jwww955ZVXGDRoEKmpqdx7771Z8iUmJkZYO7Pdu3dTvnz5HPO0a9eOHj16ADBgwACaNGnCsGHDmDJlCnfeeeehvYkClJCQQEJCXrqDi0hxcMiXjJ1zHznnxvpzBN4HjPZfhz4ecc49fQjBIMAMvEEo16Yn+HcuGQB8kj7ljH9Z+tiQ9abhBXzhD4C3/L8/OYT6iEgcSE1NpUqVKnTr1o0ePXqQmpoaMV94/7yUlBTMjBUrVnDFFVdQpUoV2rZtm+fyO3bsCHiBabqJEyfStGlTypQpQ61atfj73//O9u3b87ztSP0MQ+uezszYvXs3U6ZMybik3b9/fyD7PoTR1LF9+/Y0a9aMFStW0KFDB8qVK0ft2rV56KGH8vxeRCRYgYwyds7dF8R2wrb5iZm9DIz2R/3+APQD6gNXh2R9HjgLf2CLc+5b4Nvw7fknuzXOudeCrquIHD5SU1O5+OKLKV26NJdffjlPPvkkn332GaecckpU6/fs2ZOjjz6aUaNGHdJceKtWrQKgWrVqgBes3XfffXTq1InrrruO7777LqNOH3zwAaVKlcpzGbmZOnUqAwcOpHXr1lx7rfc/eaNG2U+0kJc6/vbbb5xzzjlcfPHFXHrppcyYMYPbb7+d5s2b07Vr18Dfi4hEJ9B7GZvZGcDJQCWytj4659zIPG6yLzCSzPcyPs85925+6yoiEu6LL77g22+/Zfz48QC0bduWOnXqkJqaGnVAeMIJJ/Dii9nNwJXVrl272LJlC/v37+fLL7/khhtuwMy45JJL2Lx5M6NHj+bss89mzpw5GRODH3vssQwdOpQXXniBAQMG5P2N5qJ3794MHjyYhg0b0rt37xzz5rWOP//8M88//zx9+vQB4Oqrr6ZevXo8++yzCghFilAg086YWVUz+wh4F3gM7xJyiv+4N+TvPHHO7XXO3eqcO9I5l+ica+2cmxeWp71zLtcRH845c84NzWsdRCR+pKamUrNmTTp06AB4VxYuu+wypk2bRlpaWlTbGDx4cJ7KvOqqq0hOTqZWrVp069Yt41Jtq1atWLhwIX/++Sc33nhjprvEXHPNNVSsWJHZs4t+IE9e65iUlJQpyCxdujStW7eOiZHVIvEsqBbCh4EWwBV4/fNWA13wJqy+CTgN0L9+IhKz0tLSmDZtGh06dMjUf69NmzaMHTuW//73v5x99tm5bqdBg0h38szeiBEjaNeuHQkJCVSvXp3jjjsuY/TyunXrADjmmGMyrVO6dGkaNmyYsbwo5bWOderUyTJrQ5UqVfjqq68KtqIikqOgAsJzgaedc/8xs2p+2kHn3A/A383sFbwpaS4PqDwRkUAtWrSIjRs3Mm3aNKZNy3qDo9TU1KgCwrJls50zP6LmzZvTqVOnPK1zqLKbPiva1s8gZDdCWfceFilaQQWElYHl/t+/+89JIcvnA6MCKktEJHCpqanUqFGDCRMmZFn2yiuv8Oqrr/LUU0/lOeDLj3r16gHw3Xff0bBhw4z0P//8kzVr1uQ5kKxSpUrE0cmRWhqjnXs16DqKSNEIKiD8GTgCwDm3z8w2ASfw1+3eauPNSSgiEnP27NnDK6+8Qs+ePTPmBAxVq1YtXnrpJWbNmsVll11WaPXq1KkTpUuX5vHHH+ecc87JCNKeffZZduzYQbdueZuIu1GjRuzYsYOvvvqKFi1aALBx40ZeffXVLHnLly8f1dQ2QddRRIpGUPcyfhfoHPL6P8BtZna3md2Dd0/htwMqS0QkULNmzWLXrl1ccMEFEZefeuqpJCcnZzsnYUFJTk7mzjvvZO7cuZxzzjlMmDCBYcOGcf3113PKKafkOgI4XK9evShfvjwXXXQRjz32GKNHj6ZNmzY0adIkS96WLVuycOFCHnnkEaZNm8Ynn0SevjXoOopI0QgqIHwEmOVPHA3eiOKP8aaMuQ/4Arg+oLJERAKVmppKYmIinTt3jri8RIkSdOvWjblz57J169ZCrVtKSgpPPPEE69ev56abbmL69Olce+21zJ8/P89zEFarVo1XX32VcuXKcdtttzFlyhRGjx7N+eefnyXvI488QsuWLRk+fHjGfIyFUUcRKRpWkB15zawykOac21VghRQSM2sKLFu2bBlNmzYtsHKiuR/s2sQrotpW8wZ1c80zffSBXPMsap+1T1W4vz/VMao6SfGVPi1IaD8xkVikY1UEli9fTrNmzQCaOeeW55Y/0Impwznnthfk9kVEREQk/4K6ZJx+T+GnzOw7M9tmZmf66dXN7HEzOymoskREREQkOIG0EJrZ8cB7eAHmJ0Dj9G0757aYWVugPJnvQSwiIiIiMSCoS8YPAduBU/Gml9kUtnw2UHhzNYiIiIhI1IK6ZHwm8KRzbjOR5xtcjzcXoYiIiIjEmKACwhLAHzksTwb2BVSWiIiIiAQoqIBwCRBxOnozKwn0wpuXUERERERiTFAB4WjgHDN7Emjmp9U0s0549zE+DnggoLJEREREJECBDCpxzs0xs/7AY8C1fvILgAE7gb7OuXeDKEtEREREgnXIAaGZjQKmOee+AnDOTTWzV/DuaXw0XuvjKmDe4XCnEhEREZHDVX5aCO8AlgFfAZhZNbzpZjo75x4OoG4iIiIiUggCu1OJzwLenoiIiIgUsKADQhGRYmny5MmYGZ9//nng216xYgUpKSmsXbs28G1Ha9SoUbz22muHvH5Q72HBggW0bduWcuXKUaVKFXr06JHrNletWkViYmKBfT4iooBQRKTArVixgvvuu6/YB4T5fQ9vvvkm55xzDvv27eOBBx7g//7v/3jnnXdo27Ytmzdvzna9m266iZIlg7qxlohEkt9vWH0zO9n/u5L/fLSZbY+U2Tm3JJ/liUisSqmUe54Cr8OOoq5Bodq9ezfly5cv6mpE7fbbb6dhw4Z88MEHlC5dGoDzzz+fk08+mQceeICxY8dmWWfevHnMmzeP2267jX/84x+FXWWRuJHfFsKRwGf+Y6GfNjEkLf3xuf8sIlIs9O/fn6SkJDZs2ED37t1JSkoiOTmZW265hbS0tEx5p02bRsuWLalQoQIVK1akefPmPPbYY4B3Kbpnz54AdOjQATPDzFi8eHHG+nPmzKFdu3aUL1+eChUq0K1bN5YvXx6xPqtWreLcc8+lQoUKXHnllQCsXLmSSy65hCOOOILExETq1KlDr1692LHDC5DNjN27dzNlypSM8vv37w/AunXrGDJkCMcccwxly5alWrVq9OzZM1NLYBDvYdu2baxYsYKLLrooIxgEOOGEEzjuuOOYNm1als9g//793HDDDdxwww00atQomo9NRA5RfloIBwRWCxGRGJSWlkaXLl1o06YNY8aMYeHChYwdO5ZGjRpx3XXXAV6fuMsvv5y//e1vPPjggwB88803fPDBB9xwww2ceeaZDBs2jMcff5y77rqL4447DiDjeerUqfTr148uXbrw4IMP8scff/Dkk0/Stm1bvvzyS+rXr59RnwMHDtClSxfatm3LmDFjKFeuHH/++SddunRh3759XH/99RxxxBFs2LCBN998k+3bt1OpUiWmTp3KwIEDad26Ndde600Vmx5gffbZZ3z44Yf06tWLOnXqsHbtWp588knat2/PihUrKFeuXCDvYd8+7+6lZcuWzbKfy5Urx/Lly/nll1844ogjMtLHjRvHb7/9xvDhw3nllVcC+1xFJKtDDgidc1OCrIiISKzZu3cvl112Gffccw8AgwcP5uSTT+bZZ5/NCAhnz55NxYoVmTdvHgkJCVm20bBhQ9q1a8fjjz9O586dad++fcay33//nWHDhjFw4EAmTZqUkd6vXz+OOeYYRo0alSl937599OzZk9GjR2ekLV26lDVr1vDyyy/To0ePjPQRI0Zk/N27d28GDx5Mw4YN6d27d6b6devWLdN64F3GPe2005g5cyZ9+vQJ5D3UrFmTypUr88EHH2Qqa+vWraxYsQKADRs2ZASEv/zyCyNHjmTMmDFUrFgxy34VkWBpUImISA4GDx6c6XW7du1YvXp1xuvKlSuze/duFixYkOdtL1iwgO3bt3P55ZezZcuWjEdCQgJt2rTh7bffzrJOeiCarlIlr+/mvHnz+OOPP/Jch9AWu/3797N161YaN25M5cqVWbIk927f0b6HEiVKMGjQIP773/9y5513snLlSr744gsuvfRS/vzzTwD27NmTsd30/oYDBw7M83sSkbxTQCgiko3ExESSk5MzpVWpUoXffvst4/WQIUNo0qQJXbt2pU6dOlx11VXMnTs3qu2vXLkSgI4dO5KcnJzpMX/+fDZt2pQpf8mSJalTp06mtAYNGnDzzTfzzDPPUL16dbp06cKECRMy+g/mZs+ePYwYMYKjjjqKMmXKUL16dZKTk9m+fXtU28jLe7j//vu5+uqreeihh2jSpAmtWrWiZMmSXH311QAkJSUB8PHHHzN16lQeffRRSpTQz5RIYdA4fhGRbES6BByuRo0aLF26lHnz5jFnzhzmzJnDc889R9++fZkyJeeeNQcPHgS8PnihfefShU+1UqZMmYgB0tixY+nfvz+vv/468+fPZ9iwYYwePZqPP/44SwAZ7vrrr+e5557jxhtv5LTTTqNSpUqYGb169cqoX1DvoXTp0jzzzDP885//5Pvvv6dmzZo0adKEK664ghIlStC4cWMAbrvtNtq1a0eDBg0yBrds2bIFgI0bN7J+/Xrq1q2ba91EJHoKCEVE8ql06dKcf/75nH/++Rw8eJAhQ4bw9NNPc88999C4cWPMIt/EKX1gR40aNejUqVO+6tC8eXOaN2/O8OHD+fDDDznjjDN46qmnMqZqya4OM2bMoF+/fpmmfNm7dy/bt2/PlC/I91CzZk1q1qwJeAN3Fi9eTJs2bTJaCNevX8+6deto0KBBlnUvuOACKlWqlKV+IpI/CghFRPJh69atVKtWLeN1iRIlaNGiBUDGyNr0uQLDg5guXbpQsWJFRo0aRYcOHShVqlSm5Zs3b85yyTrczp07KVeuXKaWuObNm1OiRImM8tPrECmISkhIwDmXKW38+PFZptYpqPcwZswYNm7cyPjx4zPSJk2alKU/5KJFixg/fjxjxozh2GOPzXZ7InJoFBCKiOTDwIED2bZtGx07dqROnTqsW7eO8ePHc+KJJ2ZMy3LiiSeSkJDAgw8+yI4dOyhTpgwdO3akRo0aPPnkk/Tp04eTTz6ZXr16kZyczPr165k9ezZnnHEGTzzxRI7lL1q0iKFDh9KzZ0+aNGnCgQMHmDp1KgkJCVxyySUZ+Vq2bMnChQt55JFHqFWrFg0aNKBNmzacd955TJ06lUqVKnH88cfz0UcfsXDhwkxBblDv4YUXXmDmzJmceeaZJCUlsXDhQqZPn87AgQMz1fXss8/O8j7TA9GzzjqLVq1aHdJnJSLZU0AoIpIPvXv3ZtKkSUycOJHt27dzxBFHcNlll5GSkpLR3++II47gqaeeYvTo0Vx99dWkpaXx9ttvU6NGDa644gpq1arFAw88wMMPP8y+ffuoXbs27dq1Y8CA3Kd7PeGEE+jSpQtvvPEGGzZsoFy5cpxwwgnMmTOHU089NSPfI488wrXXXsvw4cPZs2cP/fr1o02bNjz22GMkJCSQmprK3r17OeOMM1i4cCFdunTJVE4Q76FJkyZs27aNkSNHsmfPHo455hieeuqpjLkRRaToWPilAonMzJoCy5YtW0bTpk0LrJz6d8zONc/axCui2lbzBrl3up4++kCueRa1n5Brnr8/1TGqOknxlT7VSsOGDYu4JiI507EqAsuXL6dZs2YAzZxzy3PLr/H8IiIiInFOAaGIiIhInFNAKCIiIhLnFBCKiIiIxDkFhCIiIiJxTgGhiIiISJxTQCgiIiIS5xQQioiIiMQ5BYQiIiIicU4BoYiIiEicU0AoIiIiEucUEIqIiIjEOQWEIiJFICUlBTMr6mqIiAAKCEVEAJg8eTJmlvFITEykVq1adOnShccff5xdu3YVdRVFRApMyaKugIgcHppPaV7UVeDrfl/nexv3338/DRo0YP/+/fzyyy8sXryYG2+8kUceeYRZs2bRokWLAGoqIhJbFBCKiITo2rUrrVq1ynh95513smjRIs477zwuuOACvvnmG8qWLVuENcyfvXv3Urp0aUqU0AUiEfmLzggiIrno2LEj99xzD+vWreOFF17ISF+0aBHt2rWjfPnyVK5cmQsvvJBvvvkmy/rvv/8+p5xyComJiTRq1Iinn346Yjl79uxh2LBhVK9enQoVKnDBBRewYcMGzIyUlJRMeTds2MBVV11FzZo1KVOmDE2bNuXf//53pjyLFy/GzJg2bRrDhw+ndu3alCtXjp07d7J//37uu+8+jj76aBITE6lWrRpt27ZlwYIF+d9hIlLsqIVQRCQKffr04a677mL+/Plcc801LFy4kK5du9KwYUNSUlLYs2cP48eP54wzzmDJkiXUr18fgK+//pqzzz6b5ORkUlJSOHDgAPfeey81a9bMUkb//v2ZPn06ffr04dRTT+Wdd96hW7duWfL9+uuvnHrqqZgZQ4cOJTk5mTlz5nD11Vezc+dObrzxxkz5R44cSenSpbnlllvYt28fpUuXJiUlhdGjRzNw4EBat27Nzp07+fzzz1myZAmdO3cuiF0oIjFMAaGISBTq1KlDpUqVWLVqFQC33norVatW5aOPPqJq1aoAdO/enZNOOol7772XKVOmADBixAicc7z33nvUrVsXgEsuuYTmzTP3uVyyZAnTp0/nxhtv5NFHHwVgyJAhDBgwgP/973+Z8t59992kpaXx9ddfU61aNQAGDx7M5ZdfTkpKCoMGDcp0WXvv3r18/vnnmdJmz57Nueeey6RJk4LcTSJSTOmSsYhIlJKSkti1axcbN25k6dKl9O/fPyMYBGjRogWdO3fmrbfeAiAtLY158+bRvXv3jGAQ4LjjjqNLly6Ztj137lzACwJDXX/99ZleO+eYOXMm559/Ps45tmzZkvHo0qULO3bsYMmSJZnW6devX5Z+j5UrV2b58uWsXLnyEPeGiBxOFBCKiETp999/p0KFCqxbtw6AY445Jkue4447ji1btrB79242b97Mnj17OProo7PkC1933bp1lChRggYNGmRKb9y4cabXmzdvZvv27UyaNInk5ORMjwEDBgCwadOmTOuEbxO80dTbt2+nSZMmNG/enFtvvZWvvvoqir0gIocjXTIWEYnCTz/9xI4dO7IEaIXt4MGDAPTu3Zt+/fpFzBM+NU6kUdFnnnkmq1at4vXXX2f+/Pk888wzPProozz11FMMHDgw+IqLSEyL6YDQzMoA9wN9gCrAV8Bw51yOw+DM7GLgMuAU4AjgR+BNYKRzbntB1llEDk9Tp04FoEuXLtSrVw+A7777Lku+b7/9lurVq1O+fHkSExMpW7ZsxMuy4evWq1ePgwcPsmbNmkwtij/88EOmfMnJyVSoUIG0tDQ6deqUr/dUtWpVBgwYwIABA/j9998588wzSUlJUUAoEodi/ZLxZOBmIBW4AUgD3jKztrmsNwk4DngBGAbMBYYCH5lZ8Z1ATESKxKJFixg5ciQNGjTgyiuv5Mgjj+TEE09kypQpbN++PSPfsmXLmD9/Pueeey4ACQkJdOnShddee43169dn5Pvmm2+YN29epjLS+xROnDgxU/r48eMzvU5ISOCSSy5h5syZLFu2LEtdN2/eHNV72rp1a6bXSUlJNG7cmH379kW1vogcXmK2hdDMWgO9gFudc2P8tOeBZcBDwOk5rN7DObc4bHtfAFOAK4FnCqLOIlL8zZkzh2+//ZYDBw7w66+/smjRIhYsWEC9evWYNWsWiYmJADz88MN07dqV0047jauvvjpj2plKlSplmjPwvvvuY+7cubRr144hQ4Zw4MABxo8fT9OmTTP12WvZsiWXXHIJ48aNY+vWrRnTznz//fcAme57/MADD/D222/Tpk0brrnmGo4//ni2bdvGkiVLWLhwIdu2bcv1fR5//PG0b9+eli1bUrVqVT7//HNmzJjB0KFDA9qTIlKcxGxACPTAaxHMmBPBObfXzJ4FRpnZUc65HyOtGB4M+l7FCwiPK4C6ishhYsSIEQCULl2aqlWr0rx5c8aNG8eAAQOoUKFCRr5OnToxd+5c7r33XkaMGEGpUqU466yzePDBBzMN4mjRogXz5s3j5ptvZsSIEdSpU4f77ruPjRs3ZhnE8fzzz3PEEUfw0ksv8eqrr9KpUyf+85//cMwxx2QEogA1a9bk008/5f777+eVV15h4sSJVKtWjaZNm/Lggw9G9T6HDRvGrFmzmD9/Pvv27aNevXr84x//4NZbb83P7hORYsqcc0Vdh4jMbAFQ2zl3fFj634CFwAXOuTfysL2jge+Bu5xzow+hPk2BZcuWLaNp06Z5XT1q9e+YnWuetYlXRLWt5g3q5ppn+ugDueZZ1H5Crnn+/lTHqOokxdfq1asBaNiwYRHXJL4sXbqUk046iRdeeIErr7yyqKtTLOhYFYHly5fTrFkzgGbOueW55Y/lFsIjgY0R0tPTauVxe7fjtTjOyC2jmdUAksOSG+WxPBGRPNmzZ0+WEcHjxo2jRIkSnHnmmUVUKxGJB7EcEJYFIvVu3huyPCpmdgVwNfCQcy6aWViHAPdGu30RkSA89NBDfPHFF3To0IGSJUsyZ84c5syZw7XXXstRRx1V1NUTkcNYLAeEe4AyEdITQ5bnyszaAc8C84C7oyx7IvByWFoj4PUo1xcRybPTTz+dBQsWMHLkSH7//Xfq1q1LSkoKd98d7alLROTQxHJAuBGoHSH9SP/559w2YGYnALPwRib3cM7l3mEOcM5tAjJN9R86wk9EpCB07tyZzp07F3U1RCQOxfI8hEuBJmZWMSy9TcjybJlZI7z5BzcB5zrnfg+6giIiIiKHg1gOCGcACcC16Qn+nUsGAJ+kTzljZnXN7NjQFc3sCGA+cBDo4pyLbqZWERERkTgUs5eMnXOfmNnLwGh/1O8PQD+gPt4AkXTPA2cBodd05wIN8Sawbht2Z5Nfc7v1nYiIiEg8idmA0NcXGEnmexmf55x7N5f1TvCfb4uw7B1AAaGIiIiIL6YDQufcXuBW/5FdnvYR0jQCRERERCRKsdyHUEREREQKgQJCERERkTingFBEREQkzikgFBEBJk+ejJll+/j444+LuooiIgUmpgeViEjx8c2xxxV1FTju22/yvY3777+fBg0aZElv3LhxvrctIhKrFBCKiITo2rUrrVq1KtI67N69m/LlyxdpHUQkvuiSsYhIlNauXYuZMWbMGCZNmkSjRo0oU6YMp5xyCp999lmW/N9++y09evSgatWqJCYm0qpVK2bNmpUpT/ql6nfeeYchQ4ZQo0YN6tSpk7F8woQJNGzYkLJly9K6dWvee+892rdvT/v27QH4/fffKV++PDfccEOW8n/66ScSEhIYPXp0sDtCRA47aiEUEQmxY8cOtmzZkinNzKhWrVrG6xdffJFdu3YxaNAgzIyHHnqIiy++mNWrV1OqVCkAli9fzhlnnEHt2rW54447KF++PNOnT6d79+7MnDmTiy66KFMZQ4YMITk5mREjRrB7924AnnzySYYOHUq7du246aabWLt2Ld27d6dKlSoZQWNSUhIXXXQR//nPf3jkkUdISEjI2OZLL72Ec44rr7yyQPaViBw+FBCKiITo1KlTlrQyZcqwd+/ejNfr169n5cqVVKlSBYBjjjmGCy+8kHnz5nHeeecBcMMNN1C3bl0+++wzypQpA3hBX9u2bbn99tuzBIRVq1blv//9b0ZA9+eff3LPPfdwyimnsGjRIkqW9E7XLVq0oH///plaEfv27UtqaioLFizgnHPOyUh/4YUXOPPMM6lbt24Qu0ZEDmO6ZCwiEmLChAksWLAg02POnDmZ8lx22WUZwSBAu3btAFi9ejUA27ZtY9GiRVx66aXs2rWLLVu2sGXLFrZu3UqXLl1YuXIlGzZsyLTNa665JlPr3ueff87WrVu55pprMoJBgCuvvDJT2eAFsbVq1SI1NTUjbdmyZXz11Vf07t07n3tEROKBWghFREK0bt0610El4S1u6QHab7/9BsAPP/yAc4577rmHe+65J+I2Nm3aRO3atTNeh49sXrduHZB1dHPJkiWpX79+prQSJUpw5ZVX8uSTT/LHH39Qrlw5UlNTSUxMpGfPnjm+FxERUEAoIpJnoS15oZxzABw8eBCAW265hS5dukTMGx7olS1bNl916tu3Lw8//DCvvfYal19+OS+++CLnnXcelSpVytd2RSQ+KCAUEQlYw4YNAShVqlTEPonRqFevHuC1Nnbo0CEj/cCBA6xdu5YWLVpkyt+sWTNOOukkUlNTqVOnDuvXr2f8+PGH+A5EJN6oD6GISMBq1KhB+/btefrpp9m4cWOW5Zs3b851G61ataJatWr861//4sCBAxnpqampGZemw/Xp04f58+czbtw4qlWrRteuXQ/9TYhIXFELoYhIiDlz5vDtt99mST/99NMpUSL6/6EnTJhA27Ztad68Oddccw0NGzbk119/5aOPPuKnn37if//7X47rly5dmpSUFK6//no6duzIpZdeytq1a5k8eTKNGjXCzLKsc8UVV3Dbbbfx6quvct1112VMgSMikhsFhCIiIUaMGBEx/bnnnsuYDDoaxx9/PJ9//jn33XcfkydPZuvWrdSoUYOTTjop2zLCDR06FOccY8eO5ZZbbuGEE05g1qxZDBs2jMTExCz5a9asydlnn81bb71Fnz59oq6riIgCQhEJRBD3ES5K/fv3p3///rnmSx84Ek16w4YNmTJlSr7Kvf7667n++uszXh88eJA1a9Zw0kknRcxfunRpGjVqxGmnnZZjuSIiodSHUEQkRu3duzdLoPn888+zbdu2iK2VGzduZPbs2WodFJE8UwuhiEiM+vjjj7npppvo2bMn1apVY8mSJTz77LM0a9Ys0/yCa9as4YMPPuCZZ56hVKlSDBo0qAhrLSLFkQJCEZEYVb9+fY466igef/xxtm3bRtWqVenbty8PPPAApUuXzsj3zjvvMGDAAOrWrcuUKVM44ogjirDWIlIcKSAUEYlR9evXZ9asWbnmi7b/o4hIdtSHUERERCTOKSAUERERiXMKCEVERETinAJCERERkTingFBEREQkzikgFBEREYlzCghFRERE4pwCQhEREZE4p4BQROKemUX1WLx4ca7bmjhxIpMnTy7wOouIBEl3KhGRuDd16tRMr59//nkWLFiQJf24447LdVsTJ06kevXqunOIiBQrCghFJBATBi8q6irw96c6HtJ6vXv3zvT6448/ZsGCBVnSRUQOV7pkLCIShYMHDzJu3DiaNm1KYmIiNWvWZNCgQfz2228ZeerXr8/y5ct55513Mi4zt2/fPmP56tWr6dmzJ1WrVqVcuXKceuqpzJ49O1M5kydPxsxYu3ZtpvTFixdnuWz93nvv0bNnT+rWrUuZMmU46qijuOmmm9izZ0+mdfv3709SUhIbNmyge/fuJCUlkZyczC233EJaWlpg+0hEii+1EIqIRGHQoEFMnjyZAQMGMGzYMNasWcMTTzzBl19+yQcffECpUqUYN24c119/PUlJSdx9990A1KxZE4Bff/2V008/nT/++INhw4ZRrVo1pkyZwgUXXMCMGTO46KKL8lynl19+mT/++IPrrruOatWq8emnnzJ+/Hh++uknXn755Ux509LS6NKlC23atGHMmDEsXLiQsWPH0qhRI6677rr87yARKdYUEIqI5OL999/nmWeeITU1lSuuuCIjvUOHDpxzzjm8/PLLXHHFFXTv3p3hw4dTvXr1LJebH3jgAX799Vfee+892rZtC8A111xDixYtuPnmm7nwwgspUSJvF20efPBBypYtm/H62muvpXHjxtx1112sX7+eunXrZizbu3cvl112Gffccw8AgwcP5uSTT+bZZ59VQCgiumQsIpKbl19+mUqVKtG5c2e2bNmS8WjZsiVJSUm8/fbbuW7jrbfeonXr1hnBIEBSUhLXXnsta9euZcWKFXmuV2gwuHv3brZs2cLpp5+Oc44vv/wyS/7Bgwdnet2uXTtWr16d53JF5PCjFkIRkVysXLmSHTt2UKNGjYjLN23alOs21q1bR5s2bbKkp49cXrduHc2aNctTvdavX8+IESOYNWtWpr6MADt27Mj0OjExkeTk5ExpVapUybKeiMQnBYQiIrk4ePAgNWrUIDU1NeLy8EArP8wsYnr44I+0tDQ6d+7Mtm3buP322zn22GMpX748GzZsoH///hw8eDBT/oSEhMDqKCKHHwWEIiK5aNSoEQsXLuSMM87IdJk2kuwCunr16vHdd99lSf/2228zloPXagewffv2TPnWrVuX6fXXX3/N999/z5QpU+jbt29G+oIFC3J+MyIiEagPoYhILi699FLS0tIYOXJklmUHDhzIFLyVL18+SzAHcO655/Lpp5/y0UcfZaTt3r2bSZMmUb9+fY4//njACz4B3n333Yx8aWlpTJo0KdP20lv8nHMZac45Hnvssby/QRGJe2ohFBHJxVlnncWgQYMYPXo0S5cu5eyzz6ZUqVKsXLmSl19+mccee4wePXoA0LJlS5588kn+8Y9/0LhxY2rUqEHHjh254447eOmll+jatSvDhg2jatWqTJkyhTVr1jBz5syMEcZNmzbl1FNP5c4772Tbtm1UrVqVadOmceDAgUx1OvbYY2nUqBG33HILGzZsoGLFisycOVN9AkXkkCggFBGJwlNPPUXLli15+umnueuuuyhZsiT169end+/enHHGGRn5RowYwbp163jooYfYtWsXZ511Fh07dqRmzZp8+OGH3H777YwfP569e/fSokUL3njjDbp165aprNTUVAYNGsQDDzxA5cqVufrqq+nQoQOdO3fOyFOqVCneeOMNhg0bxujRo0lMTOSiiy5i6NChnHDCCYW2X0Tk8GChlxske2bWFFi2bNkymjZtWmDl1L9jdq551iZekWsegOYN6uaaZ/roA7nmWdR+Qq55DvWWYVJ8pE9P0rBhwyKuiUjOdKyKwPLly9NnLmjmnFueW371IRQRERGJcwoIRUREROKcAkIRERGROKeAUERERCTOKSAUERERiXMKCEVERETinAJCERE5rGg6NZG8U0AoIlExMw4cOKAfW4lpzjnS0tIy7vwiItHRN0ZEopKUlERaWhobN27Mchs1kVjgnGPTpk2kpaVRpkyZoq6OSLGiW9eJSFSqVKnCH3/8wY4dO9ixYwclS5akRIkSmFlRV00ko2UwLS2NsmXLUrNmzaKukkixooBQRKJSsmRJ6taty65du9i5cyf79+/X5WOJGWZG6dKlKVOmDDVr1tQlY5E8UkAoIlEzMypWrEjFihWLuioiIhKgmA4IzawMcD/QB6gCfAUMd84tiGLd2sCjwNl4fSXfBm5yzq0uuBqLiMSvb449Lqp8x337TQHXRETyKqYDQmAy0AMYB6wE+gNvmVkH59z72a1kZkl4AWAlYBSwH7gJeMfMTnTObS3YasthJ6VSrlmaN6iba56v+30dRG1EREQCFbMBoZm1BnoBtzrnxvhpzwPLgIeA03NYfQhwNNDaOfeZv+4cf93/A+4qwKqL5MuEwYtyzfP3pzoWQk1ERCRexGxAiNcymAZMSk9wzu01s2eBUWZ2lHPuxxzW/Sw9GPTX/dbM/gtcigJC8dW/Y3ZU+dYmBlNeVJfU2k8IpjAREZEoxXJAeBLwvXNuZ1j6p/7ziUCWgNDMSgAtgH9H2OanwNlmVsE5tyvAuopIkKK4RE/KjoKvh4hInIjlgPBIYGOE9PS0WtmsVxUoE8W632VXsJnVAJLDko8F+OGHH7JbLRB/bl6Xa57lZdKi2tbe0ntzzbNyX+7b2rhtba55li9fHk2VYk40+xui2+fa39Hp/Mg7ueZZEMX+7j7q6FzzjP1X7tv59JThueYBuPzeNlHlizXR7e/bcs3Tvc6RueYZG8XxDZB6aaT/1zPT/s59f0Nwx3hx3d+SvZB4pXQ0+S1W5xEzs1XAd865c8PSGwKr8EYMj4uw3lHAeuB259xDYcuuAp4FTnLOLc2h7BTg3ny+BREREZGidqFzblZumWK5hXAPXktfuMSQ5dmtxyGum24i8HJYWhLQBG9gyp+5rB+kRsDrwIV4gbAULO3vwqX9Xbi0vwuf9nnh0v7+S2ngKCD3ZmtiOyDcCNSOkJ7ejv5zNuttA/aF5MvLugA45zYBmyIs+iSn9QpCyG3BVjnniu91wmJC+7twaX8XLu3vwqd9Xri0v7P4MtqMsXxvn6VAEzMLvyVCm5DlWTjnDgJfA60iLG4DrNaAEhEREZG/xHJAOANIAK5NT/DvXDIA+CR9yhkzq2tmx0ZY9xQzaxWy7jFAR7JeChYRERGJazF7ydg594mZvQyM9kf9/gD0A+oDV4dkfR44C7CQtInANcBsMxuDd6eSm4FfgbEFX3sRERGR4iNmA0JfX2Akme9lfJ5z7t2cVnLO7TKz9nj3Mh6O1xK6GG9k8uYCrG9B2Azc5z9LwdP+Llza34VL+7vwaZ8XLu3vQxSz086IiIiISOGI5T6EIiIiIlIIFBCKiIiIxDkFhCIiIiJxTgGhiIiISJxTQBgFMzvFzD40s91m5szsxKKuk+SfmdU0sxlmttX/XG80s/b+3+2Lun7R0vEZPDObbGZri7oeQYt0zOdxfeff6z2u5Xc/5rPstWb2ZmGVVxTMLMXfr9WLui7xJNannSlyZlYKbzLrvcBNwB/AugC3fwVQwzk3LqhtxhMzOx04GxjnnNuex9UfBbrgTVHwC/A5cESgFSxgBX18+mXUwpsg/jXn3NIgt53HeuTnsz5sFMAxH5e0H+ODmQ0B/nDOTS7qusQ6BYS5awTUA65xzj1TANu/AmgGjCuAbceD04F7gcnA9jyu2xF43Tk3Jj3BzIpVQEjBH58AtfD28VqyuWVkIcnPZ304CfSYj2Paj/FhCLAF73OWHOiSce5q+M/bi7ISeWVm5Yq6DsVADYrZ5xpBsTw+Acws0cx0Dipch8MxHwui2o9mVr7gqyISEOecHtk88P6jcGGPxUALf9lqvEt1vwD/BqqFrV8Br+VvLbAP2AQsAE72ly+OsP21/rL2/uvLgFF+GbuBWcBRYeUsBpYBLYF38S4bjvOX1QCexbtt317gf0C/sPXr+2XdgnfZcR2wB3gHaFbUn0MOn09KhP3n/PfTGXgf76T9O/AdMMpfr3+k9cL2e/uwstoAc4Ed/v59BzgjZPlx/j57Pmy9tkAa8GBhHZ/+smPx7um9zf/cPwcuCFu/KjAG+NrfRzuBOcAJIXnaRyjDAf395WuByRHqtji9LmHb6QX8A9gAHAQqR7l/s/2s/eUlgXuAVXjftbV435syEeo2BFju5/sZmJBej7B9uzYsrRfwBbDL31dfAzcU92PeX14Z71z1o79ffgBuB0qEle+AlKL+7sfifgxZdhbe7VM3Ab+FlNkVeA/vPL4LmA00DavXEcBzwE/+57AReD39OA/5zr2Jd275FO/7vRroW9T7tQA+n+ohafX843IZUBMYACzy9/M+YAVwXdh21kb4vBb7y0rhtRCv9PfhVv9z71zU77+oHrpknLOn8X647gIeBz7DC6w6Aw3xvri/AE3x+lg1NbNT088OwFNAD+AJvIO1Gt6X+DhgCfBPoBJQBy8QA+8EFOpuvIP4Qbzg7kZgoZmd6JzbE5KvGt6P+TTgBeBXMyuL98Pc2K/DGqAnMNnMKjvnHgsrqy9eEDsBSARuABaZWXPn3K/R7rRC9ArQBLgcb/9t8dPL450wvwJG4J0sGgNn+Mvfxbsd4lS8AP35nAoxs454+/YLvD5DB/FPRmbWzjn3qXPuGzO7B3jYzGY452b5rQOTgW/9egQt4vFpZk2BD/xlD+D9AF0KvGZmlzjnXvXXbwh0x+uDuAbvJDsIeMfMjnfO/Qx849f9fmAS3g8awIeHWOd7gD/xAtEywJ/R7F+y/6zTb0/1DN69zmfg3a+8DXAn3nftovTC/QER9wILgSeBY4DrgFPM7Azn3P5IlTazzsBLwH/xAiX8bZ8BhH+PClLgx7x/NeEdoDbeMbUe73LqaOBIvHPO4aYgzx0T8Y7L+/3tYWZ9gCnAPLzjpxzecfe+mZ3knFvrrzsT7/dkPF4wUwPv96au/zpdY7xj/Vl/u1fhnde/cM4tz/PeiHFm1ggv+NuGF7BtMbPr8P6xmwUcAM4HJppZCefcBH/VG/H25e94v7fg/YaDF3TeiXfu+BSoCLQCTsb7bONPUUeksf7gr5aNHiFpZSPk6+XnaxeSth14Ipftv0lYS0RYuT8BFULSe/rpw0LSFvtpg8K2cYOffmVIWim8H/Nd6dvlrxbCP4DaIXlb++mPFPXnkMP+u4WQliI/7UbC/rvMZl0X/vkQ1kIIGPA9XuuVhR4DeP+Vzw9JK4EXMP2CF6A/AewHWhXy8bkQ7wetTEia4QWJ34eklSFrC1B9vP+W7wlJa0VIq2BY/rXkrYVwVej3J4/7N8tn7aef4Kf/Kyz9YT+9g/86Ge8Hfl7o+wb+7ucbEJI2mZDvJV7r2Q4g4TA85ofj/WAeHZY+Gu+H9qiw9VOKeh/E6H7s76e/F3qcAEnAb8CksPw18X4jJvmvK/vr35JL2WvJ+luT7H9vxxT1fg3os0lJ/xzwrnZswAvaqoTkifQ7PBdYFZa2LPRcFJK+FHizqN9rLD3Uf+cQuJCWOb8fVHXgYz/p5JCs24E2/ijNQ/W8c25XyOsZeJcRzg3Ltw+vxTLUuXjByUshdd+P15qUhHdpI9RrzrkNIXk/BT6JUFas2+4/XxhAH7UTgaOBF4FqZlbd/7zL47UWnZlehnPuIN6PQhJei9cQYLRzrtBGIJpZVbwO79OBCiH1rYYXCB1tZrX9+u7z64yZJZhZNf66RHZyxALyb4rL3LJ9IlHu3xykH5+PhKWP9Z+7+c+dgNJ43SkOhuT7F94l4G5kb7tfp8651KWobPefD+WY74kXxPyWvv/9z2AhkACcGVw1Y952/zk/545/OefSQl53xgv2Xgrbv2l459cOfr49eK3n7c2sSi5lrHDOpbfW45zbjPe9bXiIdY5VzfBar9cCnZxzv6UvCPsdruTv03eAhmZWKYptb8e7qnd0oDUuxhQQHgIzq2pmj5nZr3hf4s14l9zAuwSc7ja8A/pHM/vUn1spr1/YlaEvnPevzQ94LTmhNjjn/gxLqwesDPvxA+8yYPrybMvyfR+hrFj3H7zWsGfwLqFOM7NLD/EEn36ymIL3OYc+BuK1smV85s65VXj/3Z6Cdzlj5CG+h0PVGK/VbSRZ63ufn6cGgJmVMLObzGwl3j8UW/x8Lch8HAdpTdjrPO3fbNTDu8z8Q2iic+4XvJN+vZB84P1whub7E681Mvz7EGoi3ndhjpn9ZGb/NrNzcqlXYcrPMX80cA5Z9/9Cf3mNbNY7HAVx7sjuGF9E1n18Nv7+dc7tw7uc3NUv+10zuy2bmQ/WR0j7DcgtkCxu3sC7mtXFObczdIGZnWFmC81sN973fDNev2GI7vw1Ai9Q/97Mvjazh82sRWA1L4bUh/DQTMfrY/MwXrPz73jB9VxCgmzn3HQzew+vD9PZwK3A7WZ2sXNuTsB12pN7lvjgnNtjZmfi/efdDe/H7jK8Pmlnh/33npv0z/NWsp9yJbzf59n+cy28lrlf8lBefqXXdwxei2Ak6YHTXXiB47/x+vZtwwusxhH9P4sum/QEvBaQcOHH6aHs37zWJd+cc5v8Cb+74P1gdwUGmNnzzrl+BVVutPJ5zJfA6zP1UDbLvw+0sjEsoHNHdsd4HyKfCw6ElD/OzN7A69vbBe/7eaeZdXTOfRmyTnb1sCjqV5zMxOsbfCVe/1Ygo0/hf/H6Z9+MNxjqT7yrBTcRxfnLOfeuv50L8c7ZA4GbzGywK7gpvGKaAsI88pvy/wbc65y7PyQ9YrOzc24jXuvCRDOrgTeY5G68S4qQ+49Ypu2ameG1An0VRXXXAS38TrahrYTHhizPtixfEzJ3Zo41Efef/37/6z9uNrO78DoVd+Cvlo9orPKfdzrncl3PzAbjXSK6G6/D8tN4J5zCstp/3h9FfXsAbzvnrg5NNLPK/NXJHnI+Rn/D+y87XL2QuuQkL/s3u3qsw/sBOJq/Wr8xs5p+3daF5ANvIMnqkHylgQbkclz4LYlvAG/4LUYTgUFmNtI590NO6wYs6GN+FZAUzfF9mCnoc0e69GN8UzT72L/KMBYY6/+uLAX+D+h9CGUXd7fiBcwTzWyXc+5FP/18vKsHFzjnMlpLzaxDhG1ke/5yzm3D62r1nJkl4Q0aSsFrIY47umScd+n/mYX/J3Zj6Au/T1amZmvn3Ca8aS7KhCTvJufm7b5mViHkdQ+8kX/RtDC+hTeNwWUh9SoJXI/X6vJOWP7u6f3L/Lyt8UZrBt2aGaTd/nPl9AS/H124pf5zmQjLcvIF3gn9Fv+EkYmZJYf83QCv1Ximc24UXqf1C8ysbx7LPGT+MbYYL1A5Mnx5aH3xjmULW94Tb7RpqCz7OMQq4FQ/qErfxnnAUVFWOer9m0M93vKfbwxLv9l/nu0/L8RrRRjm/2OV7mq87+BssuH3r8zgBw3p/5Tl9ZjKr6CP+enAaWbWJXyBmVX2zxmHo4I+d6Sbh9dH9S7z7iyUSfoxbmblzCwxbPEqvEumhX2MxQqHN4PHDGCKmV3gp2f5HfZ/bwdE2MZuIpy7Inynf8e7ehKv+1othHnlnNtpZu8Ct/lf7g14zc0NwrJWAH4ysxl4c//9jtep/RS8//bSfQFcZmaP4E0b8rtz7o2Q5dvwpiZ4Dm9U2o14B+2/oqjuJLxpRCabWUu8lr4eeFMo3Bg2WAV/u++b2ZN4X4ob8eZmyu5SUiz4wn/+p5lNwxvV+zf//c7GaxWqgTfA4ye8eaai5pw7aGYD8YLi5f7nsAEvaOqAd6I/3w8w/o13ueg6f92nzewS4DEzW+i8aVwKw9/x3ufXZvYvvNawmsBpeFMcneDnexMY4b+nD4HmeJdmwlv2VuH10RlsZrvwTrCfOOfW4P0n3QOYa2bT8e6c0pu/WkVyFO3+9bNH+qzfcM79z8ymANf6rZvv4I2Q74c3UOptv6zNZjYab9qZuWY2C6+1cAjed++FHKr6jB8sLMI7jurh/WO1lJBWyUIS9DH/MHAB8KaZTfa3Xx7veOiB14d4S3YrF2MFeu5I5/9mXIc3Vc0Sv6zNeFPJdMPrszgU72rMf/3v0Qq8lrGL8L670w7pHR4G/HNEb+A1YLqZnQvMx/vn7g0zexpvIN81eHMShv8j/AVwnZkNx/uN2+ScWwSsMLPF/vJteLMppE8TF5+KephzrD+IPK1Hbbx5rH7D+6GcjncQZkzJgDea8SG8H4ydeAHhUrJOnFkeSPW35cg6MXUvvI6yv+JNC/MmUDdsG4uBZdnUvwZeoLIZb+DAV4RNH0LmialvxuuwvBev+bxFUX8GUXxGw/FO2Gn++7gK7+SxwX/PG/BGsYZPqxFp6oj0/d4+LP1EvP4sW/x9sxavA3pHf/kwf72Lw9Y7Cm+6ktmFdXz66Q3xBmpsxDtx/oR3ufOSkDxl8Poa/uwfW+8DpxI2ZYyf9wK8QTL7CZuCxj9mfvL3y/t4E6Rn2kZ29Yx2/+bwWdf300vidRJf7b/f9WQ/MfXf8YK4P/H6dE0kl4mpgUvwWnp+9Y+pdXjzjB5R3I95Pz3J31/pA4w24wUq/weUCls/pSjec6zvR/6adibiNFP+d2Au3m/GHrzg5Dmgpb88faqqb/B+L7bjzV7RM2w7a4kwXUr4d644P4g8MXX6vLq78K5cnY/X2LIHbyDPbXgthBnnBX+9mni/mzvJPDH13XijvH/DO/99g9evulRhvtdYepi/YyTGmFl74G28k8GMAi6rPt4X6lane3OKiIjEHfUhFBEREYlzCghFRERE4pwCQhEREZE4pz6EIiIiInFOLYQiIiIicU4BoYiIiEicU0AoIiIiEucUEIqIiIjEOQWEIiIiInFOAaGIiIhInFNAKCIiIhLnFBCKiIiIxDkFhCIiIiJxTgGhiIiISJxTQCgiIiIS5/4fDsL2WY/CZsEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_axis = np.arange(len(df_pollution['algorithm']))\n",
    "\n",
    "width = 0.1\n",
    "\n",
    "plt.figure(dpi=120)\n",
    "\n",
    "plt.bar(x_axis, 1/df_pollution['runtime/feat.'], width=width, label='Air Pollution')\n",
    "plt.bar(x_axis + width, 1/df_interstate['runtime/feat.'], width=width, label='Insterstate94')\n",
    "plt.bar(x_axis + (2*width), 1/df_dodgers['runtime/feat.'], width=width, label='Dodgers')\n",
    "plt.bar(x_axis + (3*width), 1/df_energy['runtime/feat.'], width=width, label='Energy')\n",
    "plt.bar(x_axis + (4*width), 1/df_tetouan['runtime/feat.'], width=width, label='Tetouan')\n",
    "\n",
    "plt.xticks(x_axis, df_pollution['algorithm'])\n",
    "plt.ylabel('Features/Runtime')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "aace4760-5bc5-4860-b70f-f46a92748ccf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>algorithm</th>\n",
       "      <th>getml</th>\n",
       "      <th>tsflex</th>\n",
       "      <th>featuretools</th>\n",
       "      <th>tsfel</th>\n",
       "      <th>tsfresh</th>\n",
       "      <th>kats</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Air_Pollution</th>\n",
       "      <td>1.0</td>\n",
       "      <td>99.3</td>\n",
       "      <td>309.7</td>\n",
       "      <td>304.8</td>\n",
       "      <td>257.0</td>\n",
       "      <td>1156.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Interstate94</th>\n",
       "      <td>1.0</td>\n",
       "      <td>59.3</td>\n",
       "      <td>157.9</td>\n",
       "      <td>224.8</td>\n",
       "      <td>215.8</td>\n",
       "      <td>653.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dodgers</th>\n",
       "      <td>1.0</td>\n",
       "      <td>70.9</td>\n",
       "      <td>201.1</td>\n",
       "      <td>285.5</td>\n",
       "      <td>255.6</td>\n",
       "      <td>732.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Energy</th>\n",
       "      <td>1.0</td>\n",
       "      <td>108.6</td>\n",
       "      <td>269.7</td>\n",
       "      <td>58.5</td>\n",
       "      <td>217.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tetouan</th>\n",
       "      <td>1.0</td>\n",
       "      <td>85.1</td>\n",
       "      <td>266.9</td>\n",
       "      <td>262.8</td>\n",
       "      <td>227.0</td>\n",
       "      <td>1061.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "algorithm     getml tsflex featuretools  tsfel tsfresh    kats\n",
       "Air_Pollution   1.0   99.3        309.7  304.8   257.0  1156.7\n",
       "Interstate94    1.0   59.3        157.9  224.8   215.8   653.3\n",
       "Dodgers         1.0   70.9        201.1  285.5   255.6   732.6\n",
       "Energy          1.0  108.6        269.7   58.5   217.0     NaN\n",
       "Tetouan         1.0   85.1        266.9  262.8   227.0  1061.5"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indices = ['Air_Pollution', 'Interstate94', 'Dodgers', 'Energy', 'Tetouan']\n",
    "\n",
    "columns = df_pollution['algorithm'].copy()\n",
    "columns.loc[0] = 'getml'\n",
    "\n",
    "df_runtime_per_feat = pd.DataFrame(index=indices, \n",
    "                                   columns=columns)\n",
    "\n",
    "data_frames = [df_pollution, df_interstate, df_dodgers, df_energy, df_tetouan]\n",
    "\n",
    "for name, df in zip(indices, data_frames):\n",
    "    df_runtime_per_feat.loc[name, :] = df['runtime/feat.'].values\n",
    "\n",
    "df_runtime_per_feat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3858416f-2a9e-458f-bb11-d56fe239b6c8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>algorithm</th>\n",
       "      <th>getml</th>\n",
       "      <th>tsflex</th>\n",
       "      <th>featuretools</th>\n",
       "      <th>tsfel</th>\n",
       "      <th>tsfresh</th>\n",
       "      <th>kats</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Air_Pollution</th>\n",
       "      <td>1.0</td>\n",
       "      <td>99.3</td>\n",
       "      <td>309.7</td>\n",
       "      <td>304.8</td>\n",
       "      <td>257.0</td>\n",
       "      <td>1156.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Interstate94</th>\n",
       "      <td>1.0</td>\n",
       "      <td>59.3</td>\n",
       "      <td>157.9</td>\n",
       "      <td>224.8</td>\n",
       "      <td>215.8</td>\n",
       "      <td>653.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dodgers</th>\n",
       "      <td>1.0</td>\n",
       "      <td>70.9</td>\n",
       "      <td>201.1</td>\n",
       "      <td>285.5</td>\n",
       "      <td>255.6</td>\n",
       "      <td>732.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Energy</th>\n",
       "      <td>1.0</td>\n",
       "      <td>108.6</td>\n",
       "      <td>269.7</td>\n",
       "      <td>58.5</td>\n",
       "      <td>217.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tetouan</th>\n",
       "      <td>1.0</td>\n",
       "      <td>85.1</td>\n",
       "      <td>266.9</td>\n",
       "      <td>262.8</td>\n",
       "      <td>227.0</td>\n",
       "      <td>1061.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "algorithm     getml tsflex featuretools  tsfel tsfresh    kats\n",
       "Air_Pollution   1.0   99.3        309.7  304.8   257.0  1156.7\n",
       "Interstate94    1.0   59.3        157.9  224.8   215.8   653.3\n",
       "Dodgers         1.0   70.9        201.1  285.5   255.6   732.6\n",
       "Energy          1.0  108.6        269.7   58.5   217.0     NaN\n",
       "Tetouan         1.0   85.1        266.9  262.8   227.0  1061.5\n",
       "                0.0    0.0          0.0    0.0     0.0     0.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_runtime_per_feat.loc['', :] = np.zeros(6)\n",
    "df_runtime_per_feat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8c85f567-6280-45ea-8fb4-1993d9bb8423",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(dpi=120, figsize=(10, 5))\n",
    "\n",
    "df_runtime_per_feat.head(5).plot(y=columns, \n",
    "                         kind='bar',\n",
    "                         ax=ax,\n",
    "                         ylabel='Runtime / Feature',\n",
    "                         xlabel='Dataset',\n",
    "                         legend=True,\n",
    "                         rot=45,\n",
    "                         grid=True\n",
    "                         );\n",
    "\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "lgd = ax.legend(handles, labels, bbox_to_anchor=(0.85,0.98))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "787a24d3-580b-4992-9af4-e5e4fc4c9177",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(dpi=120, figsize=(10, 5))\n",
    "\n",
    "df_runtime_per_feat.plot(y=columns, \n",
    "                         kind='bar',\n",
    "                         ax=ax,\n",
    "                         logy=True,\n",
    "                         ylabel='Runtime / Feature',\n",
    "                         xlabel='Dataset',\n",
    "                         legend=True,\n",
    "                         rot=45,\n",
    "                         grid=True\n",
    "                         );"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5468310c-73c6-43ef-8fb0-a34e500c633d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Solarize_Light2',\n",
       " '_classic_test_patch',\n",
       " '_mpl-gallery',\n",
       " '_mpl-gallery-nogrid',\n",
       " 'bmh',\n",
       " 'classic',\n",
       " 'dark_background',\n",
       " 'fast',\n",
       " 'fivethirtyeight',\n",
       " 'ggplot',\n",
       " 'grayscale',\n",
       " 'seaborn',\n",
       " 'seaborn-bright',\n",
       " 'seaborn-colorblind',\n",
       " 'seaborn-dark',\n",
       " 'seaborn-dark-palette',\n",
       " 'seaborn-darkgrid',\n",
       " 'seaborn-deep',\n",
       " 'seaborn-muted',\n",
       " 'seaborn-notebook',\n",
       " 'seaborn-paper',\n",
       " 'seaborn-pastel',\n",
       " 'seaborn-poster',\n",
       " 'seaborn-talk',\n",
       " 'seaborn-ticks',\n",
       " 'seaborn-white',\n",
       " 'seaborn-whitegrid',\n",
       " 'tableau-colorblind10']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "68055eac-681c-48c7-b77a-55b2a785bb9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1bb6b218-f920-493a-8d92-cc4da5da9140",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('fivethirtyeight')\n",
    "\n",
    "fig, ax = plt.subplots(dpi=120, figsize=(10, 5))\n",
    "\n",
    "df_runtime_per_feat.head(5).plot(y=columns, \n",
    "                         kind='bar',\n",
    "                         ax=ax,\n",
    "                         ylabel='Runtime / Feature',\n",
    "                         xlabel='Dataset',\n",
    "                         legend=True,\n",
    "                         rot=45,\n",
    "                         grid=True\n",
    "                         );\n",
    "\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "lgd = ax.legend(handles, labels, bbox_to_anchor=(0.85,0.98))\n",
    "\n",
    "fig.suptitle('getML vs other tools: linear scale')\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig('../assets/benchmarks_plot_linear.png');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0426a0c3-c640-4b46-9f55-66ed6fd9a896",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def plot(style):\n",
    "    \n",
    "    plt.style.use(style)\n",
    "                  \n",
    "    fig, ax = plt.subplots(dpi=120, figsize=(10, 5))\n",
    "\n",
    "    df_runtime_per_feat.plot(y=columns, \n",
    "                             kind='bar',\n",
    "                             ax=ax,\n",
    "                             logy=True,\n",
    "                             ylabel='Runtime / Feature',\n",
    "                             xlabel='Dataset',\n",
    "                             legend=True,\n",
    "                             rot=45,\n",
    "                             grid=True\n",
    "                             );\n",
    "    \n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    lgd = ax.legend(handles, labels)\n",
    "    \n",
    "    fig.suptitle('getML vs other tools: logarithmic scale')\n",
    "    \n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.savefig('../assets/benchmarks_plot_log.png');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e857127b-5580-4a9a-9598-b9899071e7cb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4636267d-5ca4-449e-a10a-610392a35f6d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# plot('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6621d98f-25ff-408f-87ff-e4d045ce43e3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# plot('tableau-colorblind10')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d360f5d5-c74e-432c-aa37-310ae4a68f47",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
